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2017 | OriginalPaper | Chapter

Making Use of External Company Data to Improve the Classification of Bank Transactions

Authors : Erlend Vollset, Eirik Folkestad, Marius Rise Gallala, Jon Atle Gulla

Published in: Advanced Data Mining and Applications

Publisher: Springer International Publishing

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Abstract

This project aims to explore to what extent external semantic resources on companies can be used to improve the accuracy of a real bank transaction classification system. The goal is to identify which implementations are best suited to exploit the additional company data retrieved from the Brønnøysund Registry and the Google Places API, and accurately measure the effects they have. The classification system builds on a Bag-of-Words representation and uses Logistic Regression as classification algorithm. This study suggests that enriching bank transactions with external company data substantially improves the accuracy of the classification system. If we compare the results obtained from our research to the baseline, which has an accuracy of 89.22%, the Brønnøysund Registry and Google Places API yield increases of 2.79pp and 2.01pp respectively. In combination, they generate an increase of 3.75pp.

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Metadata
Title
Making Use of External Company Data to Improve the Classification of Bank Transactions
Authors
Erlend Vollset
Eirik Folkestad
Marius Rise Gallala
Jon Atle Gulla
Copyright Year
2017
Book
Advanced Data Mining and Applications

Print ISBN: 978-3-319-69178-7

Electronic ISBN: 978-3-319-69179-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-69179-4_54

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